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IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)

作者： Abachizadeh, Mahdi Yazdi, Mohammad Reza Haeri Yousefi-Koma, Aghil Univ Tehran Sch Mech Engn Tehran Iran

ISBN: (纸本)9781424480302

In this paper, an efficient method based on artificial bee colony (ABC) metaheuristic is implemented for tuning PID controllers. Considering performance indices presented in the literature, benchmark plants of different orders and time delays are controlled by PID controllers with optimum gains. Results clearly demonstrate that the employed method has outperformed other techniques such as fuzzy modeling and genetic algorithm resulting in designs with minimum error, overshoot and settling time.

关键词： pid tuning artificial bee colony algorithm error minimization

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A Cooperative Approach to The artificial bee colony algorithm

A Cooperative Approach to The Artificial Bee Colony Algorith...

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2010 IEEE World Congress on Computational Intelligence

作者： El-Abd, Mohammed Amer Univ Kuwait Sci & Engn Div Safat 13034 Kuwait

ISBN: (纸本)9781424481262

The artificial bee colony (ABC) algorithm is a powerful continuous optimization tool that has been proposed in the past few years. Many studies have shown the ABC superiority in terms of performance when compared to other well-known optimization algorithms. In this paper, the implementation of a Cooperative ABC (CABC) algorithm that is based on the explicit space decomposition approach is investigated. Both the ABC algorithm and its cooperative versions are applied to a well-known set of classical benchmark functions.

关键词： artificial bee colony algorithm continuous optimization tool cooperative ABC algorithm cooperative approach optimisation space decomposition approach

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An Improved artificial bee colony algorithm for Job Shop Problem

An Improved Artificial Bee Colony Algorithm for Job Shop Pro...

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International Conference on Advanced Mechanical Engineering (AME 2010)

作者： Yao, Baozhen Yang, Chengyong Hu, Juanjuan Yin, Guodong Yu, Bo Beijing Jiaotong Univ Sch Civil Engn & Architecture Beijing 100044 Peoples R China Minist Transport Peoples Republ China Transport Management Inst Beijing 101601 Peoples R China Beijing Univ Technol Coll Architecture & Civil Engn Beijing 100022 Peoples R China Dalian Maritime Univ Transportat Management Coll Dalian 116026 Peoples R China

ISBN: (纸本)9780878492497

Job shop scheduling problem (JSP) plays a significant role for production management and combinatorial optimization. An improved artificial bee colony (IABC) algorithm with mutation operation is presented to solve JSP in this paper. The results for some benchmark problems reveal that IABC is effective and efficient compared to those of other approaches. IABC seems to be a powerful tool for optimizing job shop scheduling problem.

关键词： Job shop scheduling problem artificial bee colony algorithm Mutation operation

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An artificial bee colony algorithm for the 0-1 Multidimensional Knapsack Problem 1

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3rd International Conference on Contemporary Computing

作者： Sundar, Shyam Singh, Alok Rossi, Andre Univ Hyderabad Dept Comp & Informat Sci Hyderabad 500046 Andhra Pradesh India Univ Bretagne Sud Lab STICC F-56321 Lorient Cedex France

ISBN: (数字)9783642148347

ISBN: (纸本)9783642148330

In this paper, we present an artificial bee colony (ABC) algorithm for the 0-1 Multidimensional Knapsack Problem (MKP_01). The objective of MKP_01 is to find a subset of a given set of n objects in such a way that the total profit of the objects included in the subset is maximized, while a set of knapsack constraints remains satisfied. The ABC algorithm is a new metaheuristic technique based on the intelligent foraging behavior of honey bee swarms. Heuristic-based repair operators and local search are incorporated into our ABC algorithm. Computational results demonstrate that our ABC algorithm not only produces better results but converges very rapidly in comparison with other swarm-based approaches.

关键词： artificial bee colony algorithm combinatorial optimization heuristic multidimensional knapsack problem swarm intelligence

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A new approach for optimal reactive power flow of MTDC systems using the ABC algorithm

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TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 2017年第1期25卷 15-29页

作者： Kilic, Ulas Ayan, Kursat Ege Univ Fac Engn Dept Elect & Elect Engn Izmir Turkey Sakarya Univ Fac Comp & Informat Sci Dept Comp Engn Adapazari Sakarya Turkey

This paper presents a new approach to optimize reactive power ow of multiterminal high voltage direct current (HVDC) systems. Successful application of two-terminal DC systems worldwide makes the use of multiterminal direct current (MTDC) systems more attractive. Due to the economic and technical advantages of HVDC technology, MTDC systems have been used extensively in recent years. In this study, the artificial bee colony (ABC) algorithm is used for solution of the optimal reactive power ow problem of MTDC systems. In opposition to the current-balancing method used in the literature, this study represents a new approach for DC system power ow calculations. The proposed approach is tested on a sample IEEE MTDC test system. The results by the proposed approach are compared with those reported in the literature. Thus, the applicability and the efficiency of this approach used together with the ABC algorithm are shown.

关键词： Optimal reactive power flow high voltage direct current system multiterminal direct current system artificial bee colony algorithm

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A Dynamic Multi-Projection-Contour Approximating Framework for the 3D Reconstruction of Buildings by Super-Generalized Optical Stereo-Pairs

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SENSORS 2017年第9期17卷 2153页

作者： Yan, Yiming Su, Nan Zhao, Chunhui Wang, Liguo Harbin Engn Univ Dept Informat & Commun Engn Harbin 150001 Peoples R China

In this paper, a novel framework of the 3D reconstruction of buildings is proposed, focusing on remote sensing super-generalized stereo-pairs (SGSPs). As we all know, 3D reconstruction cannot be well performed using nonstandard stereo pairs, since reliable stereo matching could not be achieved when the image-pairs are collected at a great difference of views, and we always failed to obtain dense 3D points for regions of buildings, and cannot do further 3D shape reconstruction. We defined SGSPs as two or more optical images collected in less constrained views but covering the same buildings. It is even more difficult to reconstruct the 3D shape of a building by SGSPs using traditional frameworks. As a result, a dynamic multi-projection-contour approximating ( DMPCA) framework was introduced for SGSP-based 3D reconstruction. The key idea is that we do an optimization to find a group of parameters of a simulated 3D model and use a binary feature-image that minimizes the total differences between projection-contours of the building in the SGSPs and that in the simulated 3D model. Then, the simulated 3D model, defined by the group of parameters, could approximate the actual 3D shape of the building. Certain parameterized 3D basic-unit-models of typical buildings were designed, and a simulated projection system was established to obtain a simulated projection-contour in different views. Moreover, the artificial bee colony algorithm was employed to solve the optimization. With SGSPs collected by the satellite and our unmanned aerial vehicle, the DMPCA framework was verified by a group of experiments, which demonstrated the reliability and advantages of this work.

关键词： remote sensing 3Dreconstruction super-generalized stereo-pairs artificial bee colony algorithm

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Effective Sentiment Analysis for Opinion Mining Using artificial bee colony Optimization

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Research Journal of Applied Sciences, Engineering and Technology 2016年第8期12卷 828-840页

作者： T.M. Saravanan A. Tamilarasi Department of Computer Applications Kongu Engineering College Perundurai Erode Tamil Nadu 638052 India

Opinions play important role in the process of knowledge discovery or information retrieval and can be considered as a sub discipline of Data Mining. The huge quantity of information on web platforms put together feasible for exercise as data sources, in applications based on opinion mining and classification. An effective sentiment analysis process proposes in this research for mining and classifying the opinions. The phases of the proposed research are: (1) Data Pre-processing Phase (2) Potential Feature Extraction Phase (3) Opinion Extraction and Mining Phase and (4) Opinion Classification Phase. Initially, the datasets from various web documents get preprocessed and gives as part-of-speech tagged text. An Improved High Adjective Count (IHAC) algorithm employs on the Part-Of-Speech tagged text to extract the potential features. Improved High Adjective Count algorithm effectively optimizes the scores of the nouns to extract the potential features. An artificial bee colony (ABC) algorithm works under the IHAC algorithm for providing opinion scores and also for giving ranks for every noun. Max Opinion Score algorithm can be then helpful to extract the opinion words followed by the classification phase, in which, ID3 algorithm utilizes to classify the review into three kinds positive, negative and neutral based on the opinions. The implementation is carried out on Customer Review Datasets and Additional Review Datasets with the aid of JAVA platform and also the experimentation results are analyzed.

关键词： artificial bee colony algorithm ID3 algorithm improved high adjective count algorithm max opinion score algorithm opinion mining

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An Endmember Extraction Method Based on artificial bee colony algorithms for Hyperspectral Remote Sensing Images

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REMOTE SENSING 2015年第12期7卷 16363-16383页

作者： Sun, Xu Yang, Lina Zhang, Bing Gao, Lianru Gao, Jianwei Chinese Acad Sci Inst Remote Sensing & Digital Earth Key Lab Digital Earth Sci Beijing 100094 Peoples R China

Mixed pixels are common in hyperspectral remote sensing images. Endmember extraction is a key step in spectral unmixing. The linear spectral mixture model (LSMM) constitutes a geometric approach that is commonly used for this purpose. This paper introduces the use of artificial bee colony (ABC) algorithms for spectral unmixing. First, the objective function of the external minimum volume model is improved to enhance the robustness of the results, and then, the ABC-based endmember extraction process is presented. Depending on the characteristics of the objective function, two algorithms, artificial bee colony Endmember Extraction-RMSE (ABCEE-R) and ABCEE-Volume (ABCEE-V) are proposed. Finally, two sets of experiment using synthetic data and one set of experiments using a real hyperspectral image are reported. Comparative experiments reveal that ABCEE-R and ABCEE-V can achieve better endmember extraction results than other algorithms when processing data with a low signal-to-noise ratio (SNR). ABCEE-R does not require high accuracy in the number of endmembers, and it can always obtain the result with the best root mean square error (RMSE);when the number of endmembers extracted and the true number of endmembers does not match, the RMSE of the ABCEE-V results is usually not as good as that of ABCEE-R, but the endmembers extracted using the former algorithm are closer to the true endmembers.

关键词： hyperspectral remote sensing artificial bee colony algorithm endmember extraction spectral unmixing

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Optimization of hedging rules for hydropower reservoir operation

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SCIENTIA IRANICA 2017年第5期24卷 2242-2252页

作者： Sasireka, K. Neelakantan, T. R. SASTRA Univ Sch Civil Engn Thanjavur 613401 India SASTRA Univ Sch Civil Engn Ctr Adv Res Environm Thanjavur 613401 India Kalasalingam Univ Kalasalingam Acad Res & Educ Dept Civil Engn Krishnankoil 626126 India

Reservoir operation plays an important role in economic development of a region. Hedging operations were used for municipal, industrial, and irrigation water supplies from reservoirs in the past. However, hedging operation for hydropower reservoir operation is very rare. A practically simple and useful new form of Standard Operation Policy and a new form of hedging rules for hydropower production are introduced in this paper and demonstrated with a case study for hydropower reservoir operation of Indirasagar reservoir system in India. The performance of optimal hedging rules is compared with that of a new standard operation policies and the superiority (reliability increases by about 10%) of the hedging rules is demonstrated. When the number of decision variables is increased from 5 to 15, energy production increases by 0.7%, the spill is reduced by 16.8%, and reliability slightly decreases by 2.1%. A bi-level simulation-optimization algorithm is used for optimizing the hedging rules. For optimization, Genetic algorithm, artificial bee colony algorithm, and imperialistic competitive algorithms are utilized. The results indicate that all the three algorithms are competitive and artificial bee colony algorithm is marginally better than the other two. (C) 2017 Sharif University of Technology. All rights reserved.

关键词： Hedging rule Reservoir operation Hydropower Optimization Genetic algorithm artificial bee colony algorithm Imperialistic competitive algorithm

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Multi-machine power system stabilizer design via HPA algorithm

JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GA...

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JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY 2017年第4期32卷 1271-1285页

作者： Ekinci, Serdar Hekimoglu, Baran Batman Univ Muhendisl Mimarl Fak Bilgisayar Muhendisligi Bolumu TR-72060 Batman Turkey Batman Univ Muhendisl Mimarl Fak Elekt Elekt Muhendisligi Bolumu TR-72060 Batman Turkey

This paper describes a novel hybrid approach based on particle swarm optimization (PSO) and artificial bee colony algorithm (ABC) called HPA technique that has powerful capabilities to discover the optimistic results for optimal design of power system stabilizer (PSS) in a multi-machine power system. For achieving optimal tuning of PSS parameters, the problem of selecting PSS parameters is converted to a simple optimization problem with an eigenvalue-based objective function and is solved by using the HPA technique. The effectiveness of the proposed HPA based-PSS design is verified through eigenvalue analysis, time domain simulations and some performance indices on a 3-machine 9-bus power system under different disturbances. The results of these studies show that the HPA algorithm is an alternative and more effective optimizer for tuning of PSS parameters and enhance greatly the dynamic stability of the power system compared with PSO and ABC. Also, the potential and superiority of the HPA algorithm over PSO and ABC in terms of computational time, convergence rate and solution quality is proved.

关键词： Power system stabilizer multi-machine power system artificial bee colony algorithm particle swarm optimization hybridization

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